CN109598960A - The drive advice method of electric car leasing system - Google Patents
The drive advice method of electric car leasing system Download PDFInfo
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- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
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- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
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Abstract
The invention discloses a kind of drive advice methods of electric car leasing system, solves problem of the prior art, its technical solution includes being suitable for electric car leasing system, it is characterised in that: the following steps are included: S1, the virtual comparison driver of several integrated integrals is established by server；S2 matches one group according to the driving ability of user and virtually compares driver's progress synthetical comparison and assessment；The real-time driving data of user is obtained, and score value processing is carried out to driving data；The virtual driving data score of real-time driving data score and virtual comparison driver is compared sequence, obtains the driving data ranking of a user by S3；S4, transmits the mobile phone of corresponding driving data and correlation data to user, and provides corresponding drive advice.
Description
Technical field
The present invention relates to administrative skill field more particularly to a kind of drive advice sides of electric car leasing system of hiring a car
Method.
Background technique
Automobile rent industry is a kind of emerging transportation service industry, it because that need not handle insurance, without year checking maintenance,
The advantages that vehicle can be replaced arbitrarily replaces buying car to control enterprise or user cost, has pushed away at present in many cities to hire a car
This charter business is gone out.
In traditional car rental services, when user after vehicle using returning the car, need to specified lease point working
It returns the car under the cooperation of personnel, process of returning the car is complicated, not only reduces the efficiency of returning the car of user, also increases people from leasing company
The workload of member.
But the lease driving cost of electric car is still very high now, wherein being with regard to some, electric car is rented
Rent it is middle need a large amount of time to go to charge, therefore, saving electric quantity consumption as far as possible retains electricity as far as possible and makes busy
Time has enough vehicle participation operations just critically important, therefore, other than setting about from hardware, improves driving for user as far as possible
Reasonability is sailed, reducing by hundred kilometers of power consumption as far as possible becomes a kind of possible approach.
China Patent Publication No.: CN106250560A, publication date: 2016-12-21 discloses a kind of intelligent automobile user
Data managing method, which is characterized in that including following operative step: identification is sentenced according to the User ID that on-vehicle host obtains
Other class of subscriber assigns corresponding user right into customer data base；The class of subscriber is divided into car owner user, Che Zhujia
Belong to user, automobile friend user and Guest User；Information collection records user's vehicle habits information, by user in vehicle habits information
Pass to customer data base；Data analysis, analyzes database information, differentiates that user is accustomed to vehicle；Information feedback, according to user
It is accustomed to feature, user is provided and is accustomed to reporting with vehicle, the corresponding driving opinion of user is provided.But this technical solution can exist with
Lower problem: this technical solution can not can not comply fully with current vehicle condition and road according to the real-time use state of current masses
There is the driving opinion reasonability of user in the case where condition condition, for example, appear in wagon flow it is crowded in the case where propose
Excessive rate request can require driver to close the relatively absurd suggestion such as air-conditioning in the high temperature day that everybody opens air-conditioning,
Still there is biggish room for improvement rationally reducing on hundred kilometers of power consumption.
Summary of the invention
The purpose of the present invention is overcoming in current electric car lease that a large amount of time is needed to go to charge, so that numerous
Busy time does not have the problem of enough vehicles participate in operation, provides a kind of driving reasonability for improving user as far as possible, to the greatest extent may be used
Hundred kilometers of power consumption can be reduced, realize the driving for there are enough vehicles to participate in the electric car leasing system runed in the rush hour
Suggesting method.
To solve the above-mentioned problems, the present invention is achieved by the following scheme: a kind of electric car leasing system
Drive advice method, be suitable for electric car leasing system, comprising the following steps:
S1 is established the virtual comparison driver of several integrated integrals by server；
S2 matches one group according to the driving ability of user and virtually compares driver's progress synthetical comparison and assessment；Obtain user
Real-time driving data, and to driving data carry out score value processing；
The virtual driving data score of real-time driving data score and virtual comparison driver is compared row by S3
Sequence obtains the driving data ranking of a user；
S4, transmits the mobile phone of corresponding driving data and correlation data to user, and provides corresponding drive advice, described
Suggestion for operation by manually preset save in the server, suggestion for operation by server according to the driving data of user arrange
Number is driven in the difference of name and driving data and the virtual comparison driver to rank the first, driving data and this synthetical comparison and assessment
According to average value difference carry out the acquisition of condition query mode.
Other than setting about from hardware, according to the real use state of current masses, meet current vehicle condition and road conditions item
In the case where part, the driving reasonability of user is improved as far as possible, and reducing by hundred kilometers of power consumption as far as possible becomes a kind of possible way
Diameter.Because having references to average data public under current similar situation, the suggestion and opinion provided is more targeted, more accords with
Close current conditions, do not appear in wagon flow it is crowded in the case where propose excessive rate request, will not all open sky at everybody
It requires driver to close the relatively absurd suggestion such as air-conditioning when tune, hundred kilometers of power consumption can be reduced as far as possible.
Preferably, in S4 step, driving data includes at least hundred kilometers of power consumption, and server is public according to the hundred of user
In power consumption data ranking and hundred kilometers of power consumption datas and hundred kilometers of power consumption of virtual comparison driver for ranking the first
Difference, the average value difference of hundred kilometers of power consumption datas and hundred kilometers of power consumption datas in this synthetical comparison and assessment are looked into carry out condition
Inquiry mode obtains corresponding drive advice.
Preferably, in S1 step,
All synthesis driving datas for establishing virtual comparison driver are randomly selected the user for being really by server
It is established after driving data after the account of separation and real-time perfoming updates, the content of update includes integrated integral, setting random parameter
Power consumption calculating formula afterwards, integrated integral are carried out by virtually comparing driver by participating in synthetical comparison and assessment as real-time update.
Preferably, virtually comparison driver's integrating state variance yields is equal to the random parameter set in power consumption calculating formula
Multiplied by the proportionality coefficient manually set in advance.
Preferably, selecting the average value for using integral in every group of Comprehensive Correlation, it is comprehensive to calculate each participation in current group
The p (Q) of the user of comparison is closed, p (Q) is calculated by following calculating formula:
Comprehensive Correlation is grouped successfully if all p (Q) are more than or equal to setting value, otherwise re-starts grouping；
All total p of user (Q) in grouping are selected if at least there is a p (Q) in all groupings and be less than setting value
It is worth least packet mode to be grouped；P (Q) value be user's comprehensive score be greater than current group in average aggregate score it is general
Rate；Q is the average difference using integral in currently used person and current group,For the integrating state variance of currently used person
Value.In this way, both a more mature driver will not be fought to user, it is all new that user will not be allowed corresponding
Hand, but the driver of comprehensive selection several similar driving abilities compares, therefore the suggestion provided and opinion more have
Specific aim more meets reality and the driving ability of user.
Preferably, the data for participating in comparison further include, the spacing and vehicle of vehicle place and the predetermined area use the time
With the vehicle of budget using the difference between the time, i.e., to power consumption and return the car place and the spacing of the predetermined area, vehicle make
Ranking is carried out respectively using the difference between the time with the vehicle of time and budget, and every ranking is weighted respectively,
The weighted value of every ranking is set manually；The summation of every ranking weighted value is calculated, the total value of every ranking weighted value is
The comprehensive score value driven for this.
Preferably, virtually comparing the distance computation formula and vehicle of return the car place and the predetermined area of driver in server
Using the vehicle of time and budget using the difference calculating formula between the time by manually preset after be stored in server
In.
Preferably, server is sent to the message rewarded all participation Comprehensive Correlation personnel in the hand of user
On machine.
The beneficial effects of the present invention are: can be met according to current public real use state using method of the invention
In the case where current vehicle condition and road conditions condition, the driving reasonability of user is improved as far as possible, reduces by hundred kilometers of power consumption as far as possible
As a kind of possible approach.Because having references to average data public under current similar situation, the suggestion and meaning that provide
See more targetedly, more meet current conditions, do not appear in wagon flow it is crowded in the case where propose excessive rate request, also not
Driver can be required to close the relatively absurd suggestion such as air-conditioning when everybody opens air-conditioning, hundred public affairs can be reduced as far as possible
In power consumption.And user will not have both been allowed to fight a more mature driver, it is all new that user will not be allowed corresponding
Hand, but the driver of comprehensive selection several similar driving abilities compares, therefore the suggestion provided and opinion more have
Specific aim more meets reality and the driving ability of user.
Specific embodiment
Below by embodiment, the technical solutions of the present invention will be further described.
Embodiment 1:
A kind of drive advice method of electric car leasing system is suitable for electric car leasing system, including following step
It is rapid:
S1 is established the virtual comparison driver of several integrated integrals by server；
S2 matches one group according to the driving ability of user and virtually compares driver's progress synthetical comparison and assessment；Obtain user
Real-time driving data, and to driving data carry out score value processing；
The virtual driving data score of real-time driving data score and virtual comparison driver is compared row by S3
Sequence obtains the driving data ranking of a user；
S4, transmits the mobile phone of corresponding driving data and correlation data to user, and provides corresponding drive advice, described
Suggestion for operation by manually preset save in the server, suggestion for operation by server according to the driving data of user arrange
Number is driven in the difference of name and driving data and the virtual comparison driver to rank the first, driving data and this synthetical comparison and assessment
According to average value difference carry out the acquisition of condition query mode.
In S4 step, driving data includes at least hundred kilometers of power consumption, and server is according to hundred kilometers of power consumption of user
Difference, hundred public affairs of data rank and hundred kilometers of power consumption datas with the virtual hundred kilometers of power consumption of comparison driver to rank the first
In the average value difference of power consumption data and hundred kilometers of power consumption datas in this synthetical comparison and assessment obtained to carry out condition query mode
Obtain corresponding drive advice.
In S1 step,
All synthesis driving datas for establishing virtual comparison driver are randomly selected the user for being really by server
It is established after driving data after the account of separation and real-time perfoming updates, the content of update includes integrated integral, setting random parameter
Power consumption calculating formula afterwards, integrated integral are carried out by virtually comparing driver by participating in synthetical comparison and assessment as real-time update.
Virtual comparison driver's integrating state variance yields is equal to the random parameter set in power consumption calculating formula multiplied by preparatory
The proportionality coefficient manually set.
The average value that integral is used in every group of Comprehensive Correlation is selected, each participation Comprehensive Correlation makes in calculating current group
The p (Q) of user, p (Q.) are calculated by following calculating formula:
Comprehensive Correlation is grouped successfully if all p (Q) are more than or equal to setting value, otherwise re-starts grouping；
All total p of user (Q) in grouping are selected if at least there is a p (Q) in all groupings and be less than setting value
It is worth least packet mode to be grouped；P (Q) value be user's comprehensive score be greater than current group in average aggregate score it is general
Rate；Q is the average difference using integral in currently used person and current group,For the integrating state variance of currently used person
Value.
The data for participating in comparison further include that the spacing and vehicle of vehicle place and the predetermined area use the vehicle of time and budget
Using the difference between the time, i.e., time and pre- is used to the spacing of power consumption and return the car place and the predetermined area, vehicle
The vehicle of calculation carries out ranking using the difference between the time respectively, and every ranking is weighted respectively, every ranking
Weighted value is set manually；The summation of every ranking weighted value is calculated, the total value of every ranking weighted value is this driving
Comprehensive score value.
When virtually comparing the distance computation formula and vehicle of return the car place and the predetermined area of driver in server and using
Between with the vehicle of budget using the difference calculating formula between the time by being stored in the server after manually presetting.
Server is sent to the message rewarded all participation Comprehensive Correlation personnel on the mobile phone of user.
Querying method in the present embodiment illustrates by taking individual power saving comparation and assessment as an example, is stored in server first electronic
Several improvement ideas that automobile power saving drives, the driving phase of the corresponding electric car of each improvement idea, Mei Gegai
Be corresponding at least one querying condition into opinion, the driving phase of the electric car include boost phase, falling-rate period and
Stablize travel phase, boost phase, falling-rate period and stable travel phase are determined by the rate of acceleration change of electric car, work as electricity
It is boost phase when the acceleration positive change rate of electrical automobile is greater than the set value, when the acceleration negative sense change rate of electric car is big
It is falling-rate period when setting value, remaining travel phase is to stablize travel phase, and then, server is being borrowed in each user
Close environmental Comparison step is executed when vehicle, each user average power consumption under similar environments is recorded, in real time to average consumption
The user that amount is greater than average power consumption provides driving opinion, opinion storage is driven in the server, according to by actual power consumption amount
After improvement idea corresponding with the result queries of the difference of average power consumption in real time down to electric car or mobile phone.It is described to change
Acquisition is inquired after corresponding to the querying condition of respective stage by following calculating formula calculated result into opinion；
J=T × [C(t)-C(a)]；
J is query condition value in above formula, and improvement idea, C are determined in the range intervals in querying condition according to the value of J(t)
For real-time hundred kilometers of power consumption of user, C(a)For each user under similar environments average power consumption；Server obtains in real time
The current place for participating in power saving and driving comparation and assessment vehicle is taken, corresponding discharge coefficient T is set according to the current vehicle flow in place.
Using the method for the present embodiment, current vehicle condition and road conditions item can be met according to current public real use state
In the case where part, the driving reasonability of user is improved as far as possible, and reducing by hundred kilometers of power consumption as far as possible becomes a kind of possible way
Diameter.Because having references to average data public under current similar situation, the suggestion and opinion provided is more targeted, more accords with
Close current conditions, do not appear in wagon flow it is crowded in the case where propose excessive rate request, will not all open sky at everybody
It requires driver to close the relatively absurd suggestion such as air-conditioning when tune, hundred kilometers of power consumption can be reduced as far as possible.And both
User will not be allowed to fight a more mature driver, it is all new hand that user will not be allowed corresponding, but comprehensive selection
The driver of several similar driving abilities compares, therefore the suggestion provided and opinion are more targeted, more meets existing
Real and user driving ability.
Electric car leasing system in the present embodiment is identical as existing general electric car leasing system, all includes
Central server, handheld terminal, new-energy automobile, monitoring module, matching module, the authentication being installed on inside new-energy automobile
Module and geography information module.
Above-mentioned embodiment is only a preferred solution of the present invention, not the present invention is made in any form
Limitation, there are also other variations and modifications on the premise of not exceeding the technical scheme recorded in the claims.
Claims (8)
1. a kind of drive advice method of electric car leasing system is suitable for electric car leasing system, it is characterised in that: packet
Include following steps:
S1 is established the virtual comparison driver of several integrated integrals by server；
S2 matches one group according to the driving ability of user and virtually compares driver's progress synthetical comparison and assessment；
The real-time driving data of user is obtained, and score value processing is carried out to driving data；
The virtual driving data score of real-time driving data score and virtual comparison driver is compared sequence, obtained by S3
To the driving data ranking of a user；
S4, transmits the mobile phone of corresponding driving data and correlation data to user, and provides corresponding drive advice, the behaviour
Work suggest by manually preset save in the server, suggestion for operation by server according to the driving data ranking of user with
And difference, driving data and the driving data in this synthetical comparison and assessment of driving data and the virtual comparison driver to rank the first
The difference of average value carries out the acquisition of condition query mode.
2. the drive advice method of electric car leasing system according to claim 1, it is characterised in that: in S4 step
In, driving data includes at least hundred kilometers of power consumption, and server is public according to hundred kilometers of power consumption data rankings of user and hundred
In the difference of power consumption data and virtual hundred kilometers of power consumption of comparison driver for ranking the first, hundred kilometers of power consumption datas and this
The average value difference of hundred kilometers of power consumption datas obtains corresponding drive advice to carry out condition query mode in secondary synthetical comparison and assessment.
3. the drive advice method of electric car leasing system according to claim 1, it is characterised in that: in S1 step
In,
All synthesis driving datas for establishing virtual comparison driver randomly select user really by server and drive
It is established after data after the account of separation and real-time perfoming updates, after the content of update includes integrated integral, sets random parameter
Power consumption calculating formula, integrated integral are carried out by virtually comparing driver by participating in synthetical comparison and assessment as real-time update.
4. the drive advice method of electric car leasing system according to claim 3, it is characterised in that: virtual comparison is driven
The person's of sailing integrating state variance yields is equal to the random parameter set in power consumption calculating formula multiplied by the proportionality coefficient manually set in advance.
5. the drive advice method of electric car leasing system according to claim 4, it is characterised in that:
It selects to calculate each user for participating in Comprehensive Correlation in current group in every group of Comprehensive Correlation using the average value of integral
P (Q), p (Q) calculated by following calculating formula:
Comprehensive Correlation is grouped successfully if all p (Q) are more than or equal to setting value, otherwise re-starts grouping；
All total p of user (Q) values are selected in grouping if at least there is p (Q) in all groupings and be less than setting value most
Few packet mode is grouped；P (Q) value is the probability that user's comprehensive score is greater than average aggregate score in current group；Q
The difference integrated is used to be average in currently used person and current group,For the integrating state variance yields of currently used person.
6. the drive advice method of electric car leasing system according to claim 5, it is characterised in that:
The data for participating in comparison further include that the spacing and vehicle of vehicle place and the predetermined area are made using the vehicle of time and budget
With the difference between the time, i.e., time and budget are used to the spacing of power consumption and return the car place and the predetermined area, vehicle
Vehicle carries out ranking using the difference between the time respectively, and every ranking is weighted respectively, the weighting of every ranking
Value is set manually；The summation of every ranking weighted value is calculated, the total value of every ranking weighted value is the comprehensive of this driving
Close score value.
7. the drive advice method of electric car leasing system according to claim 6, it is characterised in that:
Virtually compared in server the distance computation formula and vehicle of return the car place and the predetermined area of driver using the time with
The vehicle of budget using the difference calculating formula between the time by manually preset after store in the server.
8. the drive advice method of electric car leasing system according to claim 7, it is characterised in that: server is right
The message that all participation Comprehensive Correlation personnel are rewarded is sent on the mobile phone of user.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110334696A (en) * | 2019-07-31 | 2019-10-15 | 爱驰汽车有限公司 | Cockpit pseudo-experience system, method, equipment and storage medium |
Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20080100268A1 (en) * | 2006-11-01 | 2008-05-01 | Gye-Jong Lim | Battery management system and driving method thereof |
| CN103587375A (en) * | 2009-05-06 | 2014-02-19 | 福特全球技术公司 | Climate control system and method for optimizing energy consumption of vehicle |
| US20140278617A1 (en) * | 2013-03-15 | 2014-09-18 | Rockwell Automation Technologies, Inc. | Systems and methods for updating confidence values for energy information associated with an industrial automation system |
| CN104986160A (en) * | 2015-06-16 | 2015-10-21 | 北京亿利智慧能源科技有限公司 | Electric automobile driving behavior guide instrument |
| CN104992364A (en) * | 2015-07-28 | 2015-10-21 | 行之有道汽车服务股份有限公司 | Unattended electric car rental system and rental method |
| CN105160883A (en) * | 2015-10-20 | 2015-12-16 | 重庆邮电大学 | Energy-saving driving behavior analysis method based on big data |
| CN105978055A (en) * | 2015-03-13 | 2016-09-28 | 苏州宝时得电动工具有限公司 | Power supply device and power transmission device |
| CN106143702A (en) * | 2016-07-21 | 2016-11-23 | 柳州国淘科技有限公司 | One has illumination functions bicycle safe monitor and alarm system and control method |
| CN106228254A (en) * | 2016-07-25 | 2016-12-14 | 成都云科新能汽车技术有限公司 | A kind of electric motor coach method for running based on global optimization |
| CN106275152A (en) * | 2016-07-21 | 2017-01-04 | 柳州国淘科技有限公司 | One has illumination functions bicycle safe monitor and alarm system and control method |
| CN106372884A (en) * | 2016-08-31 | 2017-02-01 | 杭州金通公共自行车科技股份有限公司 | Pile-less bike low electric quantity excitation system |
| CN107000751A (en) * | 2014-11-26 | 2017-08-01 | 通腾远程信息公司 | Device and method for providing suggestion drive speed |
| US20170243485A1 (en) * | 2012-04-24 | 2017-08-24 | Zetta Research and Development LLC, ForC series | V2v safety system using learned signal timing |
-
2017
- 2017-10-18 CN CN201710974557.9A patent/CN109598960B/en active Active
Patent Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20080100268A1 (en) * | 2006-11-01 | 2008-05-01 | Gye-Jong Lim | Battery management system and driving method thereof |
| CN103587375A (en) * | 2009-05-06 | 2014-02-19 | 福特全球技术公司 | Climate control system and method for optimizing energy consumption of vehicle |
| US20170243485A1 (en) * | 2012-04-24 | 2017-08-24 | Zetta Research and Development LLC, ForC series | V2v safety system using learned signal timing |
| US20140278617A1 (en) * | 2013-03-15 | 2014-09-18 | Rockwell Automation Technologies, Inc. | Systems and methods for updating confidence values for energy information associated with an industrial automation system |
| CN107000751A (en) * | 2014-11-26 | 2017-08-01 | 通腾远程信息公司 | Device and method for providing suggestion drive speed |
| CN105978055A (en) * | 2015-03-13 | 2016-09-28 | 苏州宝时得电动工具有限公司 | Power supply device and power transmission device |
| CN104986160A (en) * | 2015-06-16 | 2015-10-21 | 北京亿利智慧能源科技有限公司 | Electric automobile driving behavior guide instrument |
| CN104992364A (en) * | 2015-07-28 | 2015-10-21 | 行之有道汽车服务股份有限公司 | Unattended electric car rental system and rental method |
| CN105160883A (en) * | 2015-10-20 | 2015-12-16 | 重庆邮电大学 | Energy-saving driving behavior analysis method based on big data |
| CN106143702A (en) * | 2016-07-21 | 2016-11-23 | 柳州国淘科技有限公司 | One has illumination functions bicycle safe monitor and alarm system and control method |
| CN106275152A (en) * | 2016-07-21 | 2017-01-04 | 柳州国淘科技有限公司 | One has illumination functions bicycle safe monitor and alarm system and control method |
| CN106228254A (en) * | 2016-07-25 | 2016-12-14 | 成都云科新能汽车技术有限公司 | A kind of electric motor coach method for running based on global optimization |
| CN106372884A (en) * | 2016-08-31 | 2017-02-01 | 杭州金通公共自行车科技股份有限公司 | Pile-less bike low electric quantity excitation system |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110334696A (en) * | 2019-07-31 | 2019-10-15 | 爱驰汽车有限公司 | Cockpit pseudo-experience system, method, equipment and storage medium |
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